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Consumer Insights - don’t we have a smarter way?

Whether it’s Spotify for Brands or JWT Intelligence x Snap Inc, every new week brings a hot new take on some, emerging misaligned or misunderstood consumer demographic. And across broader media, we’re using the terminologies of consumer groups more frequently. We all know why millennials don’t buy houses… And just today I have read headlines stating 100% of Gen Zs have smartphones and another that decries Gen Zs are not as digitally smart as you think they are. Huh?

We’re obsessed with the millennial work ethic and Boomers’ retirement plans. It’s natural as an industry focused on consumer behaviours that we’ll need to generalise in order to make sense of mass behaviours. I too devour these reports, hungry for fresh insights and warning signs of new movements. But how, in such a time of data, are we still speaking in such broad swathes?

Just last week, Vogue was calling for the need for a more nuanced way of classifying types of streetwear. And The High Low’s Dolly & Pandora were lamenting over the singularity of the (often unlikeable) female mid-30s characters in shows like Fleabag and Girls. But we aren’t asking the same of our framework for consumer demographics.

There would be very little common ground between a Gen Z in rural China and a 16 year old from the South Bronx, and almost as much distance between my 11 and 18 year old London-dwelling cousins. So why are we hell bent on understanding them as a mass? Is it not in fact dangerous to assume such a narrow view?

These very reports speak of the increased need for diversity, inclusivity, customisation and personalisation. And yet we’re still happy to lump the largest consumer group the world has ever seen together, bundling them up as Gen Z, summarised in five key takeaways for your brand, or yours, or yours. You all get a Gen Z!

It’s time we got smarter, mapping out consumer groups based on data that considers geography, race, religion, socioeconomics, education, politics and exposure. We have commonly used personality tests that are more complex than the decks and documents driving the worlds’ biggest manufacturers.

I want to work in a consumer insights landscape where we’re mapping out multifaceted, intelligent and hyper-personalised demographic insights, in 4D. Hell, we could even have AI versions of these coded consumer groups that are machine learning - truly growing with the behaviours of their own unique tribes.